Triple

T13952942
Position Surface form Disambiguated ID Type / Status
Subject Mexican Federal Highway 110 E335576 entity
Predicate connectsCity P4245 FINISHED
Object Yurécuaro
Yurécuaro is a town in the state of Michoacán, Mexico, known as a regional agricultural center near the border with Jalisco.
E1144684 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Yurécuaro | Statement: [Mexican Federal Highway 110, connectsCity, Yurécuaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yurécuaro
Context triple: [Mexican Federal Highway 110, connectsCity, Yurécuaro]
  • A. Uruapan
    Uruapan is a major city in the Mexican state of Michoacán, known for its avocado production and proximity to the Paricutín volcano.
  • B. Juanacatlán
    Juanacatlán is a municipality in the state of Jalisco, Mexico, known for its proximity to the Santiago River and the Juanacatlán Falls.
  • C. Juanacatlán
    Juanacatlán is a Mexico City Metro station on Line 1, located near the Condesa and San Miguel Chapultepec neighborhoods.
  • D. Yautepec
    Yautepec is a municipality in the Mexican state of Morelos known for its warm climate, agriculture, and growing tourism and residential developments.
  • E. Tecomán
    Tecomán is a city in the Mexican state of Colima known for its agricultural production, particularly limes, and its proximity to Pacific coast beaches.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Yurécuaro
Triple: [Mexican Federal Highway 110, connectsCity, Yurécuaro]
Generated description
Yurécuaro is a town in the state of Michoacán, Mexico, known as a regional agricultural center near the border with Jalisco.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Yurécuaro
Target entity description: Yurécuaro is a town in the state of Michoacán, Mexico, known as a regional agricultural center near the border with Jalisco.
  • A. Uruapan
    Uruapan is a major city in the Mexican state of Michoacán, known for its avocado production and proximity to the Paricutín volcano.
  • B. Juanacatlán
    Juanacatlán is a municipality in the state of Jalisco, Mexico, known for its proximity to the Santiago River and the Juanacatlán Falls.
  • C. Juanacatlán
    Juanacatlán is a Mexico City Metro station on Line 1, located near the Condesa and San Miguel Chapultepec neighborhoods.
  • D. Yautepec
    Yautepec is a municipality in the Mexican state of Morelos known for its warm climate, agriculture, and growing tourism and residential developments.
  • E. Tecomán
    Tecomán is a city in the Mexican state of Colima known for its agricultural production, particularly limes, and its proximity to Pacific coast beaches.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e146720819085d0f5eae558b7a4 completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd19164481909c2f35fbebf6150e completed May 9, 2026, 7:07 a.m.
NEDg Description generation batch_69fede23eab88190ab026382ba3ea06b completed May 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69fede93c6a88190afc35f9e3f16a6f2 completed May 9, 2026, 7:13 a.m.
Created at: April 9, 2026, 10:17 p.m.